Description:

mcerp 0.12

Code: https://github.com/tisimst/mcerp
Documentation: (not online yet, for now, see the doc folder on Github)
License: BSD-3-Clause


Overview
mcerp is a stochastic calculator for Monte Carlo methods that uses
latin-hypercube sampling to perform non-order specific
error propagation (or uncertainty analysis).
With this package you can easily and transparently track the effects
of uncertainty through mathematical calculations. Advanced mathematical
functions, similar to those in the standard math module, and statistical
functions like those in the scipy.stats module, can also be evaluated
directly.
If you are familiar with Excel-based risk analysis programs like @Risk,
Crystal Ball, ModelRisk, etc., this package will work wonders for you
(and probably even be faster!) and give you more modelling flexibility with
the powerful Python language. This package also doesn’t cost a penny,
compared to those commercial packages which cost thousands of dollars for a
single-seat license. Feel free to copy and redistribute this package as much
as you desire!


Main Features

Transparent calculations. No or little modification to existing
code required.
Basic NumPy support without modification. (I haven’t done extensive
testing, so please let me know if you encounter bugs.)
Advanced mathematical functions supported through the mcerp.umath
sub-module. If you think a function is in there, it probably is. If it
isn’t, please request it!
Easy statistical distribution constructors. The location, scale,
and shape parameters follow the notation in the respective Wikipedia
articles and other relevant web pages.
Correlation enforcement and variable sample visualization capabilities.
Probability calculations using conventional comparison operators.
Advanced Scipy statistical function compatibility with package
functions. Depending on your version of Scipy, some functions might not
work.



Installation
mcerp works on Linux, MacOS and Windows, with Python 2.7 or with Python 3.5 or later.
To install it, use pip:
pip install mcerp
The mcerp dependencies should be installed automatically if using pip,
otherwise they will need to be installed manually:

NumPy : Numeric Python
SciPy : Scientific Python
Matplotlib : Python plotting library



See also

uncertainties : First-order error propagation
soerp : Second-order error propagation



Contact
Please send feature requests, bug reports, or feedback to
Abraham Lee.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

Share

• Share on Facebook
• Share on Twitter